|
|
Absolute deviation, 绝对离差0 e& c3 B* J- X3 W6 [- |5 ^2 o; T
Absolute number, 绝对数6 m, I$ Y; V$ L9 _3 ] A3 t1 S
Absolute residuals, 绝对残差) S+ }) B& m8 {6 q- A
Acceleration array, 加速度立体阵
4 k5 ^( M1 e& C2 i1 J2 fAcceleration in an arbitrary direction, 任意方向上的加速度
5 U# O/ C2 Y0 k3 PAcceleration normal, 法向加速度
7 O1 e- \2 K" e+ b: h& HAcceleration space dimension, 加速度空间的维数
* A) V4 Q' U# b" @2 R8 DAcceleration tangential, 切向加速度! X9 d6 ^& w- w5 d& X% w8 h
Acceleration vector, 加速度向量
% ]7 n: d/ b/ c- U! V9 QAcceptable hypothesis, 可接受假设
5 P! Z+ w) B+ E9 M; IAccumulation, 累积
7 x% p. O- z. q$ t2 O! dAccuracy, 准确度
v2 \' X$ B( W1 F' Z% b/ YActual frequency, 实际频数+ `6 J y% e" L( F0 Q$ S
Adaptive estimator, 自适应估计量
' I- E2 P$ q# F7 y7 v2 r) RAddition, 相加: I9 P3 W( R5 w. s9 x, ~
Addition theorem, 加法定理8 r% o$ S, K% Y1 M, O. F
Additivity, 可加性5 u0 W6 q8 C ~9 s" x
Adjusted rate, 调整率5 h1 R" C$ C& h7 v3 Q H5 W- F
Adjusted value, 校正值( I! f2 {7 Y" n% u) c/ o3 A
Admissible error, 容许误差! Y/ \& |6 t2 T, K/ B: w
Aggregation, 聚集性4 E0 X- A- c, E5 g. R6 W
Alternative hypothesis, 备择假设7 F- a4 g7 _3 P7 i% c0 M
Among groups, 组间8 m2 s+ `# T: |, A
Amounts, 总量5 W8 A. J ?- s7 ?+ d9 L
Analysis of correlation, 相关分析
: I8 w0 P K) b+ G! k& X/ t1 n+ |Analysis of covariance, 协方差分析
/ z6 v7 ~, o x5 F# J4 g+ FAnalysis of regression, 回归分析8 C* x2 q1 k( ^7 t1 q6 ]* `
Analysis of time series, 时间序列分析7 Q% U# a, L. e9 m
Analysis of variance, 方差分析
9 V v, _' I _ X& D; ^1 GAngular transformation, 角转换5 y7 Y3 ~* ^9 i/ X* Q" l5 {8 S
ANOVA （analysis of variance）, 方差分析- I0 U, H) s- q- M/ i6 V# H
ANOVA Models, 方差分析模型
* d5 q' B# B% @; F( _Arcing, 弧/弧旋* w/ n0 `8 V# r7 I
Arcsine transformation, 反正弦变换
$ p! u3 S5 _& ]- h4 N9 bArea under the curve, 曲线面积
6 w, M2 A ]8 C: t7 iAREG , 评估从一个时间点到下一个时间点回归相关时的误差 * m& k) y( R0 V1 {6 q7 h
ARIMA, 季节和非季节性单变量模型的极大似然估计
* Y. ] x7 @1 [0 e# P6 ?Arithmetic grid paper, 算术格纸0 D1 V3 A4 H0 a
Arithmetic mean, 算术平均数
! U G. z/ U6 b0 B+ IArrhenius relation, 艾恩尼斯关系
; `7 L- d5 R: `+ S8 P: d% c4 pAssessing fit, 拟合的评估* M6 O/ ]; q( ~1 L
Associative laws, 结合律
: U& k' i$ t3 O( B) {% L1 J0 B7 ~Asymmetric distribution, 非对称分布
" N: `+ I2 K0 z# bAsymptotic bias, 渐近偏倚
6 |) U4 {& Y: A1 x2 k3 E2 EAsymptotic efficiency, 渐近效率1 D6 M6 W( R* `. \- F V4 ]
Asymptotic variance, 渐近方差$ [* L. ?* Z7 F( z3 |; m t
Attributable risk, 归因危险度
: ^0 t. A# @" L- o) p7 v% ]Attribute data, 属性资料
; C, v5 c2 x8 @" U/ rAttribution, 属性
0 N; B& U0 {/ [4 LAutocorrelation, 自相关4 D: m! }% f+ Q' T# `$ I& W
Autocorrelation of residuals, 残差的自相关) n; ~/ D% Q5 g4 R; |9 K
Average, 平均数
- w2 }; e( e NAverage confidence interval length, 平均置信区间长度
' y8 q, M5 Q- J! h* R$ XAverage growth rate, 平均增长率
- q1 G& _! a& O3 G% CBar chart, 条形图+ N8 t; F& q$ i9 n# y( x
Bar graph, 条形图
4 `1 s0 W! _. i* P6 I+ \4 UBase period, 基期
' h" d" ?( ?4 u+ m! z2 Y: s. @Bayes' theorem , Bayes定理- ^% v# L2 l; [& y& I5 d7 J4 E+ a9 U; l
Bell-shaped curve, 钟形曲线
' o" I6 \5 w6 I% z' I: |* @Bernoulli distribution, 伯努力分布' O; P" F' K' e: S; H# v3 T
Best-trim estimator, 最好切尾估计量* z/ o/ C: O( Q9 N$ l
Bias, 偏性
9 B& P7 `" c: wBinary logistic regression, 二元逻辑斯蒂回归
* _( P) L: M; WBinomial distribution, 二项分布
0 z: Q' p9 n' V3 X. jBisquare, 双平方+ J7 ]* H; q; G3 D
Bivariate Correlate, 二变量相关
9 S D: P* m8 k' H; sBivariate normal distribution, 双变量正态分布: W% Z+ ~6 u- \
Bivariate normal population, 双变量正态总体
% ?1 T/ ?9 R; @' x8 Y, f8 QBiweight interval, 双权区间( K0 f" N' K2 H0 E( `
Biweight M-estimator, 双权M估计量
% I# h! R1 p8 F' G9 E3 dBlock, 区组/配伍组- E7 b& W* y7 t* p
BMDP(Biomedical computer programs), BMDP统计软件包
' |) S9 [: }3 s% P2 g3 n+ {Boxplots, 箱线图/箱尾图8 t9 i: x5 T. Y. `/ ]; ]
Breakdown bound, 崩溃界/崩溃点
& h& Y% | `) J& l O6 RCanonical correlation, 典型相关
2 N+ o e+ o2 v0 jCaption, 纵标目* S! H* g+ n& Y! |$ i& Z7 V& |
Case-control study, 病例对照研究
: D: A" s& j- F) ?+ eCategorical variable, 分类变量/ L5 B& W! \$ I1 E) {
Catenary, 悬链线0 K7 `. B- A9 ?" L3 C! j) @
Cauchy distribution, 柯西分布7 Y1 e- `, `* u9 n' l
Cause-and-effect relationship, 因果关系% r) L5 j4 S" m* f- A9 A
Cell, 单元4 f8 m1 Q4 [$ F- v+ t7 ?
Censoring, 终检8 v2 r m4 `- L; L* h
Center of symmetry, 对称中心* I5 s# `- I% ~7 [. d- c1 X: l) ~
Centering and scaling, 中心化和定标
1 c6 c3 ~: o% O) {2 d' c( iCentral tendency, 集中趋势 d1 U+ V/ P& d8 M% P- T, y
Central value, 中心值
- O7 z5 P6 r, [CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测% ?; f7 d8 j2 v; R4 u+ K
Chance, 机遇
: @$ g8 u4 [$ X* T! H& d- sChance error, 随机误差
) g/ A+ l; ]6 G; ?Chance variable, 随机变量
4 ?! m; {# j7 `) Q$ k: UCharacteristic equation, 特征方程
; S& Y: Y! U% f1 P6 X3 v; }Characteristic root, 特征根7 K4 M$ R+ X( S% _- Q
Characteristic vector, 特征向量! w) B! y' ^9 y$ Z# P3 ^- j! b
Chebshev criterion of fit, 拟合的切比雪夫准则
. [. e( d1 S- M8 O7 hChernoff faces, 切尔诺夫脸谱图; m+ @# t0 n; K! N: a/ Y
Chi-square test, 卡方检验/χ2检验
W ~7 f0 c: _4 s3 m+ W/ ?/ z, A- yCholeskey decomposition, 乔洛斯基分解; Y# p1 A( k( {- I# t2 g
Circle chart, 圆图 & J6 i5 H5 p- Z( Q) N! E
Class interval, 组距) s, ]9 O0 h( ], r
Class mid-value, 组中值
$ {5 Q4 z2 X4 H' fClass upper limit, 组上限
1 B1 C8 a r4 k6 r( |0 R) }% \Classified variable, 分类变量
4 w3 `. k2 Q1 a, | g( W. E5 ^& f% hCluster analysis, 聚类分析1 H+ U. ^4 U2 P# l
Cluster sampling, 整群抽样 Y" Q# a* U8 j" f+ ~$ E
Code, 代码
) a6 x. C" Q+ R# a9 f- ]0 ]Coded data, 编码数据
4 i% W2 B% z& L% z9 I, x# u! ]Coding, 编码
9 O- I6 C. F: E+ C3 u" i' t) _% \Coefficient of contingency, 列联系数
2 t* k+ W( @. V& {7 WCoefficient of determination, 决定系数# v' O6 j: P/ ^7 G+ r+ s
Coefficient of multiple correlation, 多重相关系数
j; J& L% {9 l. T- b) ?9 tCoefficient of partial correlation, 偏相关系数) x* Y" ^) q2 l# I
Coefficient of production-moment correlation, 积差相关系数
& C9 q; v% z( Q Z+ T1 s4 dCoefficient of rank correlation, 等级相关系数, \, P/ o! L3 O8 Z
Coefficient of regression, 回归系数3 O! @$ J9 j$ p i+ P
Coefficient of skewness, 偏度系数
' Q: u8 i7 h- FCoefficient of variation, 变异系数
1 a2 L+ i# K6 J+ cCohort study, 队列研究$ q( C, N: a5 S: d
Column, 列
6 y; V/ v9 k6 [( [Column effect, 列效应
c! P/ r) h$ y9 }7 q, UColumn factor, 列因素
4 e$ R3 I' N+ G0 t* H: K. JCombination pool, 合并. ^! N, m. r. I6 {! m& Q
Combinative table, 组合表8 b/ F! W. o1 C% e3 O
Common factor, 共性因子# E d5 H( [- H p
Common regression coefficient, 公共回归系数, [. B6 _. F, v9 R
Common value, 共同值# J4 @$ g0 P0 [& Z1 Q3 V# }
Common variance, 公共方差5 `8 q# u) m! X7 J; U- p
Common variation, 公共变异) S4 c) ^, f" r5 k
Communality variance, 共性方差
$ r3 @# ^0 i: w8 uComparability, 可比性9 D% v; E6 _0 ?* b# d
Comparison of bathes, 批比较
7 z9 O m/ G: N2 GComparison value, 比较值
6 U+ s5 X ?% @Compartment model, 分部模型) q, I. z) D N* V' N# N6 [
Compassion, 伸缩
0 r: s0 @5 x/ [+ \Complement of an event, 补事件
0 ~0 w7 l! j: G" W, o! aComplete association, 完全正相关9 j+ Q8 x! ~8 g$ ^9 A% Z
Complete dissociation, 完全不相关
% S; e2 r- q, B7 T. j p7 KComplete statistics, 完备统计量% Z: b4 X0 k3 t0 z
Completely randomized design, 完全随机化设计- W' c- v7 V& O F$ k
Composite event, 联合事件
; g4 o/ m" B) L* l( j8 M# ~Composite events, 复合事件; j, A& f4 O2 m- `3 g
Concavity, 凹性
' L7 J7 _4 u$ I# u( @, m! RConditional expectation, 条件期望
' W- ~4 i' v) ?3 C: RConditional likelihood, 条件似然1 g) l& z8 f. _# o: E4 {8 Y7 O [
Conditional probability, 条件概率
( Y' L# z" @2 W3 x2 c h1 E# lConditionally linear, 依条件线性3 c# }1 r7 s. d$ V. H
Confidence interval, 置信区间
" P) O$ z% G) M" c9 u9 k' uConfidence limit, 置信限
/ [- H @5 w) c& I% i4 IConfidence lower limit, 置信下限
/ z# c+ z7 J3 ^6 rConfidence upper limit, 置信上限* w) _( z* ?' {* F' A; p
Confirmatory Factor Analysis , 验证性因子分析
% G$ {$ z+ X# {7 u. kConfirmatory research, 证实性实验研究; R1 w9 ]& f3 [# R* H) ]0 k& z
Confounding factor, 混杂因素
3 F# y3 j3 w" c8 X5 N' _Conjoint, 联合分析* S- B9 z# y4 s& W/ x; B$ S
Consistency, 相合性
" b- c1 O! W7 p9 rConsistency check, 一致性检验
7 G$ C+ G8 ] D# FConsistent asymptotically normal estimate, 相合渐近正态估计
$ G5 e1 l" H9 N! vConsistent estimate, 相合估计( H6 y- L5 E" p0 e2 A
Constrained nonlinear regression, 受约束非线性回归. B$ k& j: l4 f6 z
Constraint, 约束( F! C9 e X5 t$ o$ m' Y0 u- e
Contaminated distribution, 污染分布
9 x( y) ~0 l+ d5 q! s9 @. kContaminated Gausssian, 污染高斯分布 a4 _: X9 g9 }! q
Contaminated normal distribution, 污染正态分布
- t# ?3 ^# K8 D) LContamination, 污染
/ e% z, l) s5 J4 A% gContamination model, 污染模型4 c, ^* F/ K0 c$ w6 C W
Contingency table, 列联表! r- w0 j, |3 X: ^8 p7 J' ~
Contour, 边界线1 T- R+ J* r& M @
Contribution rate, 贡献率* s3 ?9 z: V5 S# z; }/ B/ d
Control, 对照7 A( l) a3 B. d3 Z
Controlled experiments, 对照实验( {7 r" R" g$ q- T+ b
Conventional depth, 常规深度- [1 h. _: p* J6 e5 C0 {
Convolution, 卷积& f% a$ _( M9 x7 o
Corrected factor, 校正因子$ h# ?) n! w1 T$ c+ s- r
Corrected mean, 校正均值
6 S# M& o2 U) }7 k3 C+ r3 k$ ]3 {Correction coefficient, 校正系数9 t+ @, J# C4 d& N- ^& w$ C/ W! U9 Z
Correctness, 正确性
* T( M; U' s& d9 ?# {4 jCorrelation coefficient, 相关系数
' I' H3 ^+ u$ |3 @: ACorrelation index, 相关指数: W9 q2 [+ i0 `% J1 j4 m- A
Correspondence, 对应
0 K0 l$ M+ k) a5 a7 lCounting, 计数/ G9 I: S# Q5 t7 H8 w) W
Counts, 计数/频数, W w+ x' \- M9 r
Covariance, 协方差 F# {% j6 O5 K
Covariant, 共变
+ o. d8 ~( ]* E) @0 P' z6 t. QCox Regression, Cox回归7 ^0 r( ] `+ B0 x$ f# G
Criteria for fitting, 拟合准则
* [; \: Q3 [$ N ^6 t# oCriteria of least squares, 最小二乘准则
: U9 N) g) @3 j4 g$ pCritical ratio, 临界比
8 j+ g' {* T. V1 {& Q* [Critical region, 拒绝域- W6 A; @! K- E' y0 O9 P& Q
Critical value, 临界值
3 v8 G# P; F$ _5 @# O' W, ?Cross-over design, 交叉设计
$ o, X6 ~; i" f* Y8 `Cross-section analysis, 横断面分析
: P, F x$ ?2 d. j$ @Cross-section survey, 横断面调查
0 W6 j0 `4 Q# C" A+ x! K/ \1 ^: DCrosstabs , 交叉表 % P7 ~7 |& E( c' j
Cross-tabulation table, 复合表
( f5 ~' W Q9 |0 J1 l. s* NCube root, 立方根
! G* Y& ?1 A3 B6 JCumulative distribution function, 分布函数
* y6 h. d5 C# _" H; `1 iCumulative probability, 累计概率
" B% k; G0 q. ?! Z6 F7 g' G& z- f- YCurvature, 曲率/弯曲0 p' W5 @0 ~; X
Curvature, 曲率7 D9 [$ N/ v- \
Curve fit , 曲线拟和 5 @ o! B. h# I! x" @1 Q( j
Curve fitting, 曲线拟合/ p& i) z6 s0 X" r, a5 z; G, E
Curvilinear regression, 曲线回归9 ^6 k4 ?+ B) D5 H& f
Curvilinear relation, 曲线关系
s3 T7 b4 J b) S$ E7 D8 u0 ~1 tCut-and-try method, 尝试法9 V: G$ v$ F+ p- D( o. b
Cycle, 周期
; U% M* f5 e# e8 t- I& `% L" E' UCyclist, 周期性" L& k+ { D; V* N: r, Z
D test, D检验
5 W3 N. Z$ M) |) X3 RData acquisition, 资料收集
6 u# z) j3 B! ^& z4 ^2 z9 SData bank, 数据库
L0 ?5 {% `' Q* r8 bData capacity, 数据容量
3 x1 C# B! n) M: p2 P& o& W# MData deficiencies, 数据缺乏0 E/ t9 u }6 f- r
Data handling, 数据处理
8 m8 b+ W/ Y6 L7 R1 f- wData manipulation, 数据处理
~/ G; }, z) C m' ?Data processing, 数据处理
8 ]& C: |# O3 Y/ l1 F9 R' ?Data reduction, 数据缩减
, X/ y" {5 @# S. [! ]) ~; LData set, 数据集
3 l \+ J6 x) v+ n5 S8 ?) p8 {1 uData sources, 数据来源; |' z) z& `+ y9 R( o* _
Data transformation, 数据变换: M# K8 Y6 S" w) D n
Data validity, 数据有效性
# T. i0 {. L+ T l% O( a. i/ Q/ {Data-in, 数据输入
* W7 F" D, }% \Data-out, 数据输出3 G3 _* B. @( a0 O; {0 [/ P& R+ Y
Dead time, 停滞期$ z5 S! ^$ k& t5 i7 @% {: W2 r
Degree of freedom, 自由度
& l7 o. z# r9 [$ HDegree of precision, 精密度! y; v) k7 d3 ?% A' m8 J
Degree of reliability, 可靠性程度$ ~3 ^5 i. q& J2 z8 c# X) e
Degression, 递减
. ~" P1 V& C( e6 B; ]Density function, 密度函数
7 S0 ~' ]0 b! C& C6 k: R7 pDensity of data points, 数据点的密度
. @' y9 j# K- g# X; Y* j8 YDependent variable, 应变量/依变量/因变量
3 e, ~" V/ m. ^ T: | i; |0 UDependent variable, 因变量- d' ] q) r# `/ ?7 Y) w
Depth, 深度& W' @0 L1 N4 l& W3 Y
Derivative matrix, 导数矩阵
+ V+ D7 I0 D7 ?6 U7 z; vDerivative-free methods, 无导数方法
5 g2 G4 L' v+ Q* Q* E; v; ?Design, 设计! o$ Y8 d7 b% r
Determinacy, 确定性
$ g' G2 h+ n t3 a) tDeterminant, 行列式7 H. C& {- m8 Z+ Y5 k
Determinant, 决定因素
& z" F3 n1 t |' \5 r6 I* o$ IDeviation, 离差1 z' ]; h. v7 Z8 x
Deviation from average, 离均差
1 s4 ]! @* t! I6 T! J# gDiagnostic plot, 诊断图
- m0 l5 ^3 ?( {Dichotomous variable, 二分变量. u9 U# g3 S$ G! w! _1 t0 t% t# h
Differential equation, 微分方程
6 ], _! `+ l! M" X" e2 FDirect standardization, 直接标准化法
7 i) c+ s! d8 Q$ Z# |" Q$ l8 O8 K. UDiscrete variable, 离散型变量8 y# _: {% `+ A+ f9 W
DISCRIMINANT, 判断
6 d; V0 b6 l' g% uDiscriminant analysis, 判别分析
4 H+ I1 B. O" ?6 u, SDiscriminant coefficient, 判别系数
- G0 ]/ x. E x' S0 yDiscriminant function, 判别值
) F7 b- ^9 d4 n" oDispersion, 散布/分散度! u7 Q2 {* ~# d) Z0 y. m+ A$ v* e
Disproportional, 不成比例的
; n6 P1 l9 C3 Z( rDisproportionate sub-class numbers, 不成比例次级组含量8 N& Y& V+ t( s% I+ a
Distribution free, 分布无关性/免分布& ~" c3 W8 G1 w" C
Distribution shape, 分布形状# d4 M1 }) @. L3 I2 z7 Q
Distribution-free method, 任意分布法9 P! q4 M; J. b( i" _
Distributive laws, 分配律, l4 L3 O) h! n0 J7 r
Disturbance, 随机扰动项
. W0 c9 L( l0 k V/ V4 hDose response curve, 剂量反应曲线
i4 R# G/ Y- H6 R% QDouble blind method, 双盲法
/ X1 A! o% M5 `5 ~* cDouble blind trial, 双盲试验! M9 k6 @- F* [% c
Double exponential distribution, 双指数分布
1 L1 ~! s/ U- ? P. B7 R, gDouble logarithmic, 双对数
: }8 I$ V3 Z E# ~6 ^Downward rank, 降秩# \; v/ u/ w" E
Dual-space plot, 对偶空间图
/ X) D4 O! {, t* p8 i; Y- W% LDUD, 无导数方法
3 h- H7 _) p3 R$ _: p2 C& e% {) |Duncan's new multiple range method, 新复极差法/Duncan新法
) s1 c/ b: u/ m6 B8 O) Y; CEffect, 实验效应3 t) o& b: ?8 @7 i% H
Eigenvalue, 特征值
0 f+ K6 E* f" {, r4 P i" VEigenvector, 特征向量' Z0 j1 G# Q% g4 ^3 f
Ellipse, 椭圆9 B: ~3 f# @/ ^( e% j
Empirical distribution, 经验分布
* q9 G9 h8 ?: x6 o- p% X6 JEmpirical probability, 经验概率单位
. l- V; e3 J0 W; N$ q- T5 ]Enumeration data, 计数资料
; o/ ^3 I: W3 m+ sEqual sun-class number, 相等次级组含量
* ?: D4 T6 B9 c# x, K: p6 i' yEqually likely, 等可能( Z6 n9 Y8 F4 G( n9 k9 M& G
Equivariance, 同变性/ y+ h5 J) t- p% R
Error, 误差/错误
: y4 Q5 d$ V" f3 { `9 K7 A3 WError of estimate, 估计误差
, {2 n5 ^" U1 Z% {- t' H4 |Error type I, 第一类错误
; y. l5 e. z- J2 LError type II, 第二类错误
- `% }/ u N6 QEstimand, 被估量6 k7 ~2 v+ ]. ^* {7 U
Estimated error mean squares, 估计误差均方
! o. T6 ], Z8 e8 l0 vEstimated error sum of squares, 估计误差平方和: r9 e- V8 v4 c. d2 {. C( K
Euclidean distance, 欧式距离
. r& z! V! _# F( oEvent, 事件! Y* }+ F. x& a0 s9 w2 y, x
Event, 事件
: R' O; a$ E3 w" u, `Exceptional data point, 异常数据点
' H. b& D" f2 O4 Y5 H; ]# EExpectation plane, 期望平面
3 e# ^$ v( E: q: k: j( RExpectation surface, 期望曲面
( U5 H8 ?8 n4 N8 t Q& |. wExpected values, 期望值$ u z1 d$ Q. Y; e* }7 o
Experiment, 实验5 M+ R$ W" q/ K1 R
Experimental sampling, 试验抽样
. P7 T9 P9 C6 L' YExperimental unit, 试验单位
8 ^6 T6 Q' s* DExplanatory variable, 说明变量
5 K, ?9 Z/ I% V3 x2 ~Exploratory data analysis, 探索性数据分析/ j- H" }2 p# I5 ?
Explore Summarize, 探索-摘要- v3 e8 `" @' C1 z# [
Exponential curve, 指数曲线5 S8 B" d- g2 x$ }! ^" p
Exponential growth, 指数式增长, ?( h& r7 k# e
EXSMOOTH, 指数平滑方法
, L; V7 U$ w8 o% y: R8 l& G7 GExtended fit, 扩充拟合
9 f0 M" l/ t& b7 E' uExtra parameter, 附加参数7 M2 D5 a- B2 N# o9 b% |
Extrapolation, 外推法% N1 Y0 _1 }, _: w
Extreme observation, 末端观测值
V* G& \. Q2 j# uExtremes, 极端值/极值
/ N1 H7 q/ F9 l) I' X9 HF distribution, F分布
% t0 [/ I4 W4 i1 oF test, F检验
$ n; p. l% i% w. lFactor, 因素/因子
# ?/ e9 H% P: H& a* J3 @1 K- {& UFactor analysis, 因子分析6 _* A9 y& o) l& e; h: J4 _6 W" A+ J
Factor Analysis, 因子分析: A: X, G& c9 L) Q( b2 H# E5 e
Factor score, 因子得分
+ ]$ Q. A8 _. X9 n, I% _- K1 hFactorial, 阶乘, x4 `$ O5 f; D7 g! r
Factorial design, 析因试验设计
$ p1 H3 G b% c0 r9 EFalse negative, 假阴性 j6 R( n& O; d+ p% x" ~* u9 I, T
False negative error, 假阴性错误
/ T7 H k" h" u5 n1 w( eFamily of distributions, 分布族2 h L" I9 F. e7 _2 E# z2 l
Family of estimators, 估计量族
* J j% w& B X$ oFanning, 扇面2 @+ \5 u) J! a$ u8 s! r
Fatality rate, 病死率
3 ]$ r) _( |7 t" j/ KField investigation, 现场调查
/ d% `3 U: q) t- t# AField survey, 现场调查9 n& [6 U' j1 J( M, K7 ?/ j }6 O7 @
Finite population, 有限总体- [ x' Q( f5 A6 F# W% {# I5 E
Finite-sample, 有限样本+ _% J" {: d; Q3 {, l
First derivative, 一阶导数
+ `+ T" x! b/ L/ b- s. q$ k5 oFirst principal component, 第一主成分
/ i# h% w2 c8 [& f: zFirst quartile, 第一四分位数
2 D: T* B! V% I$ [Fisher information, 费雪信息量
% c' V1 t. k* F/ T3 o. OFitted value, 拟合值: t+ X4 ^$ U2 t8 D# q
Fitting a curve, 曲线拟合
0 C3 `. f! v% o' q( E! IFixed base, 定基7 Z, w d& ~; B
Fluctuation, 随机起伏 \8 x9 `( g8 x3 ~; J
Forecast, 预测3 k1 @0 K1 b: R$ J/ N( g3 A
Four fold table, 四格表6 Y( p, T" ^& e7 `
Fourth, 四分点# w9 K) ?& R( |7 {3 h+ ^
Fraction blow, 左侧比率
* E9 d! G7 c, d% I; H- VFractional error, 相对误差% e3 O8 i& M- E3 b( L
Frequency, 频率
F( P9 r @% C# L9 iFrequency polygon, 频数多边图- |, P" H& I2 L* O% n, {1 o
Frontier point, 界限点
% p Y& O6 p- C, K* nFunction relationship, 泛函关系- b3 C8 z; R0 Z! q
Gamma distribution, 伽玛分布: ?% K6 _& }( \, @5 a
Gauss increment, 高斯增量
# g1 `8 l9 B3 x" f" l. G6 O1 eGaussian distribution, 高斯分布/正态分布
+ G) N9 }9 v) @) |3 XGauss-Newton increment, 高斯-牛顿增量6 c0 T6 h3 p% d6 N# E) s1 @: _+ e
General census, 全面普查; ]+ t3 d8 t& a8 C
GENLOG (Generalized liner models), 广义线性模型 3 c- \7 E6 e, A+ v$ P" \0 ]2 M' L' z
Geometric mean, 几何平均数
" N6 g4 U" u& |) F8 F6 |Gini's mean difference, 基尼均差 g4 Q6 t$ S2 o, y+ u2 B
GLM (General liner models), 一般线性模型 # q$ Z0 n$ n0 I% G& i4 W
Goodness of fit, 拟和优度/配合度
% h+ ^$ _0 \3 s# QGradient of determinant, 行列式的梯度
0 Y1 B) M! p6 ^: t" j$ AGraeco-Latin square, 希腊拉丁方7 }1 @2 \$ t @9 G; l
Grand mean, 总均值
; h+ w Q8 A tGross errors, 重大错误9 }/ r5 ]0 ]2 E8 h8 E4 Q7 j
Gross-error sensitivity, 大错敏感度
1 }" X0 J6 a5 k$ z5 b. ZGroup averages, 分组平均, e% _6 b. a l' L6 @% J, @
Grouped data, 分组资料
" x7 ^4 j2 H# W4 ZGuessed mean, 假定平均数 Z' `* J: f Z/ s# T. @
Half-life, 半衰期
y6 m, g5 b. D% }' T) m1 R ?/ RHampel M-estimators, 汉佩尔M估计量
' ]. |4 B" E' G+ S4 ^: [6 YHappenstance, 偶然事件! r4 B# C3 \& r+ C' s1 ?) t
Harmonic mean, 调和均数0 o, ^- h/ n+ d6 Q
Hazard function, 风险均数4 P' b: T. E; {
Hazard rate, 风险率
' o) B! i7 Q! e3 Q0 HHeading, 标目
2 ^6 B' G2 J; n7 T2 Z8 M; rHeavy-tailed distribution, 重尾分布
3 e$ I0 b' P6 l, v+ U8 ZHessian array, 海森立体阵$ f. l' r, Q d% f7 ]8 c
Heterogeneity, 不同质7 D4 ?) ~3 Q/ N; J5 g R
Heterogeneity of variance, 方差不齐 9 A, l' ^7 r1 T7 x( S2 @! Y& t
Hierarchical classification, 组内分组
7 u- |% B2 ~! }/ k7 l6 w1 d* I1 `5 @Hierarchical clustering method, 系统聚类法! \. _' e B" M; m, i( [
High-leverage point, 高杠杆率点
4 N9 O" K: D/ L. Z. b% P4 fHILOGLINEAR, 多维列联表的层次对数线性模型3 E( p- Z$ S; x# o1 d4 R1 M
Hinge, 折叶点
( _4 `% y6 I" g' D) ZHistogram, 直方图
. B+ L7 @( f! S$ `. h3 H* o/ q* nHistorical cohort study, 历史性队列研究 ( h* X) a& p" A8 J
Holes, 空洞" G$ s% b6 V5 \5 v) {+ |
HOMALS, 多重响应分析
- L: A5 [5 O$ @* {% {Homogeneity of variance, 方差齐性. l' z; m* a4 u2 d, M+ E& ?
Homogeneity test, 齐性检验: M7 ~+ a8 a4 N% V& T
Huber M-estimators, 休伯M估计量( M+ ]/ N1 z1 s$ w
Hyperbola, 双曲线* r7 l' @3 p0 W5 w
Hypothesis testing, 假设检验% K0 H* O( @6 t$ V: d3 J# m
Hypothetical universe, 假设总体
% p* u$ D, k' ?% K" i; I& {Impossible event, 不可能事件
0 o' e/ C# o# X; y* kIndependence, 独立性
6 h/ A" V% z2 c2 F8 ?) n: w2 E; BIndependent variable, 自变量) l4 h' [2 u9 x1 X/ g' z
Index, 指标/指数
1 a- n2 C% L! ~& NIndirect standardization, 间接标准化法
+ D4 [; m8 M. U9 VIndividual, 个体. O* S6 @8 w* L% O
Inference band, 推断带
# H- }" ], b3 I! a) SInfinite population, 无限总体
1 _' K7 }* D2 ?( h7 N, p0 bInfinitely great, 无穷大
2 H% A( |* P0 u. H; Y5 JInfinitely small, 无穷小 q3 N1 z% i8 y1 T
Influence curve, 影响曲线
# ~( e. ]3 x. F' V, ?. WInformation capacity, 信息容量4 x/ _! C: Z% Z, W3 [% A2 @! F
Initial condition, 初始条件
" m4 h" Q4 J2 o6 B3 lInitial estimate, 初始估计值
4 i# R) i2 d$ J: CInitial level, 最初水平
1 m% g6 s% n/ h% xInteraction, 交互作用
8 J2 c0 w& J: y* B4 V* P' rInteraction terms, 交互作用项& N; K% M* M/ l: v7 e3 t
Intercept, 截距
C$ x. A& Q4 fInterpolation, 内插法
8 r$ V- F' R6 |% ?) @' fInterquartile range, 四分位距
7 `( [! j3 _" b$ }Interval estimation, 区间估计
/ C( `/ m5 t5 {4 R4 m# |: L+ S, \Intervals of equal probability, 等概率区间
/ o! p+ f- c# xIntrinsic curvature, 固有曲率
. `. l/ P, K( m2 Q N& rInvariance, 不变性6 K a0 k( S8 M, T! Y
Inverse matrix, 逆矩阵
0 b7 P( v5 y+ O5 ZInverse probability, 逆概率
! a- w& \) i: S6 v# |. @: N* R3 q; fInverse sine transformation, 反正弦变换* V2 O& [5 }+ J e
Iteration, 迭代
- n4 ]/ F) H. U$ ^" UJacobian determinant, 雅可比行列式2 u# T1 ~; x, o1 P% y) U- t
Joint distribution function, 分布函数
% V- z: t; c2 f! Z& B2 UJoint probability, 联合概率
( ]* P* c- O1 h! H0 LJoint probability distribution, 联合概率分布, X% k9 V0 d2 Z, m( ?0 z
K means method, 逐步聚类法
( Y" p: [/ u4 u$ |Kaplan-Meier, 评估事件的时间长度 ! i& Q6 f; J# |7 y3 u5 |
Kaplan-Merier chart, Kaplan-Merier图 n. O8 _" i; S+ x, `# @0 N
Kendall's rank correlation, Kendall等级相关
' t$ H$ x, D* d7 A+ o7 IKinetic, 动力学
% n0 |# k3 [. Q, NKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验* \6 E0 e/ i9 O0 r
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
' g5 U/ A0 b* _- @- _! f- OKurtosis, 峰度
; J4 ` y4 h+ I/ e: X+ J, `Lack of fit, 失拟
& }. k- a3 a+ S$ X6 V& PLadder of powers, 幂阶梯 y/ t# ?. x8 b5 y
Lag, 滞后
/ z0 K: F* L, P& w; F+ |" CLarge sample, 大样本
/ B4 _. [' o- N! g; S/ B( OLarge sample test, 大样本检验
5 L7 y: N; K8 F! f' @+ {- e' g$ N' ~! VLatin square, 拉丁方/ W& I0 P; g4 n/ K' B9 C
Latin square design, 拉丁方设计
8 X1 t! i; |( }5 h3 c& O, iLeakage, 泄漏
) u9 r/ W/ Q% A dLeast favorable configuration, 最不利构形; n' n1 c, [) |4 E r8 [; N
Least favorable distribution, 最不利分布
8 w) s$ ~, u U+ B7 n" FLeast significant difference, 最小显著差法
/ ? r8 Y8 w/ ^1 L/ a; H. ~Least square method, 最小二乘法
+ {# @6 _4 W/ NLeast-absolute-residuals estimates, 最小绝对残差估计0 R( |" P) {4 R: i% b
Least-absolute-residuals fit, 最小绝对残差拟合& ~- [6 g' n8 B' ]5 ~9 E, E2 g: e
Least-absolute-residuals line, 最小绝对残差线& e) E2 s; g1 `* U0 K9 q
Legend, 图例
# Q8 p0 ~1 ~& s+ t' R" ML-estimator, L估计量) R, A- P9 c4 T* T0 ]
L-estimator of location, 位置L估计量
- D1 ~( _1 o6 m8 F4 xL-estimator of scale, 尺度L估计量
( p" l7 q+ a) `. w9 s$ FLevel, 水平
0 C/ J# [/ s4 E" y5 ^6 W8 }Life expectance, 预期期望寿命
6 Z- u+ r; P5 v6 N% F0 N& lLife table, 寿命表& Y) Z; t3 y. i/ w
Life table method, 生命表法% T0 P+ n3 V! v( F _! \) j5 r
Light-tailed distribution, 轻尾分布
/ I1 e# v$ n& C9 q0 Q# R, xLikelihood function, 似然函数
6 n9 [1 d8 b/ h& y* C7 {Likelihood ratio, 似然比" }& p! p3 J2 s8 W' G
line graph, 线图
5 h9 }0 Q0 y! j$ D0 r0 Q% y2 uLinear correlation, 直线相关
/ |- F( \1 W* n8 R \0 NLinear equation, 线性方程
0 S/ m5 I" N8 _$ N/ _" S8 D6 Z7 CLinear programming, 线性规划
5 s- P9 j D1 ~Linear regression, 直线回归
- A( K1 u+ s7 S$ J& [Linear Regression, 线性回归: W4 s _4 u* V: _: C% g
Linear trend, 线性趋势
: d3 e7 p1 X! ~9 y: U% \Loading, 载荷
* l5 ]8 b2 U' T+ @$ _* L N" YLocation and scale equivariance, 位置尺度同变性! ~4 W) ?: F9 k2 S2 K- D
Location equivariance, 位置同变性
7 {/ ~% W, o" E0 r1 N5 X4 x3 C5 wLocation invariance, 位置不变性
5 c1 i5 Y7 W1 wLocation scale family, 位置尺度族6 _" Q8 V* q9 a1 p i, W) ~1 N3 Z+ z
Log rank test, 时序检验
8 ^. O2 p+ D, {' [; o8 fLogarithmic curve, 对数曲线. m5 q8 T, Z# O* _! A# K
Logarithmic normal distribution, 对数正态分布
; t5 X. v! ?- l5 S" X2 t/ j* _8 R- xLogarithmic scale, 对数尺度; u: N9 o( o* W
Logarithmic transformation, 对数变换2 o4 j9 M* Y$ {9 @, _ n8 Q3 x! l
Logic check, 逻辑检查
& Y- M& `) o% h4 _9 j# jLogistic distribution, 逻辑斯特分布# z3 Y. N) u. k, Z& @
Logit transformation, Logit转换
3 r- Q S J. j' c1 ?' |( ]LOGLINEAR, 多维列联表通用模型 & O( P- {8 H1 g1 W; v* r
Lognormal distribution, 对数正态分布
7 w2 Q) X. T2 ]7 T8 ~Lost function, 损失函数
0 d5 C4 ^* C, l7 g7 G$ G" rLow correlation, 低度相关9 u: {- p4 `) J- i% `6 E9 p1 w. w Z
Lower limit, 下限
6 f2 ~8 ~1 W. x& m* T. q4 B& V$ KLowest-attained variance, 最小可达方差. N/ M4 b" i" O9 _) B0 C, E
LSD, 最小显著差法的简称
$ t$ |, T& s; I( u% j5 c3 ]Lurking variable, 潜在变量
$ y" P2 J3 o [6 B& U& ?Main effect, 主效应
( W& r& @# k: x# ~4 v, T. A3 w$ ~1 ZMajor heading, 主辞标目
5 Y3 W7 C; K9 ^9 K7 r1 oMarginal density function, 边缘密度函数( q. i; y2 s6 z& }. H3 @
Marginal probability, 边缘概率
P$ G% ]' y% l" yMarginal probability distribution, 边缘概率分布
5 f$ {) v8 k- s3 K* gMatched data, 配对资料* E$ G: e" I, v0 l' ^& I
Matched distribution, 匹配过分布
2 u, `* c6 ^" b4 V3 JMatching of distribution, 分布的匹配
2 V& {! n J2 Y& s9 J) k" x4 j" u- CMatching of transformation, 变换的匹配
( z7 g' O: p# T3 ZMathematical expectation, 数学期望
8 t I2 M" r& \Mathematical model, 数学模型
8 J; |* W' Q u7 _: {$ D! z. R& }2 pMaximum L-estimator, 极大极小L 估计量
7 g* ~& c( h+ B( \* j, c. c CMaximum likelihood method, 最大似然法, `" k: C% [& j& r8 X, x
Mean, 均数
( H; _$ J# [) ?8 j3 H& B- ]Mean squares between groups, 组间均方2 r% l. x2 `3 d/ S7 H7 M5 i5 ~
Mean squares within group, 组内均方+ B ]1 D' k% t6 H P# R' I! j
Means (Compare means), 均值-均值比较& }6 x. h( k# Y2 ], m
Median, 中位数
) J; l# A4 t, `6 {Median effective dose, 半数效量+ F# k) i+ c& B6 F$ T, I" h4 W" h& [9 _
Median lethal dose, 半数致死量0 I/ ~6 r5 q" B
Median polish, 中位数平滑
/ i4 Z% Y& R& g6 ?1 W \* W- {0 oMedian test, 中位数检验( G$ h \5 c% m% f
Minimal sufficient statistic, 最小充分统计量
, F' ~9 g* H- @$ |+ O" KMinimum distance estimation, 最小距离估计+ B& w& r9 v* G$ o0 n
Minimum effective dose, 最小有效量
2 |2 t4 x- R6 u s3 V5 J) sMinimum lethal dose, 最小致死量0 q2 b [, Y, h
Minimum variance estimator, 最小方差估计量0 f/ b% }: O7 r; o: a6 C
MINITAB, 统计软件包* I9 I* ]3 n2 ~# y
Minor heading, 宾词标目
* ^6 q$ I, x B" ~9 pMissing data, 缺失值3 t3 H7 Y! F6 i- {7 T
Model specification, 模型的确定2 Y1 `# a! ]: b/ `; f9 w
Modeling Statistics , 模型统计. r) T9 d, u2 y+ W' B2 o% h% C( V
Models for outliers, 离群值模型4 z+ w5 H/ `- z) m- `
Modifying the model, 模型的修正
9 ^7 |+ ]' M% f# a3 N$ b6 jModulus of continuity, 连续性模) [' J2 V+ V. i4 X$ | k7 ?# c
Morbidity, 发病率 4 u! F. \0 O8 Z1 M6 r# `, x0 V
Most favorable configuration, 最有利构形7 P- m* Z4 h" m. @
Multidimensional Scaling (ASCAL), 多维尺度/多维标度
, i& ~; Z7 I5 v% e$ |: iMultinomial Logistic Regression , 多项逻辑斯蒂回归( f: O; g& H' i, t
Multiple comparison, 多重比较! ]/ v8 Q; I3 U, M4 ^# D
Multiple correlation , 复相关( s! Y$ k# Q0 ]" v2 N
Multiple covariance, 多元协方差
* B. V% ]( [0 N1 nMultiple linear regression, 多元线性回归
' d0 I/ ]# o! U; xMultiple response , 多重选项6 o6 D: V% t5 v% S) ~) A7 F
Multiple solutions, 多解: w4 M& j, i& Y1 M
Multiplication theorem, 乘法定理/ \4 G% B3 E" I/ h, P% l
Multiresponse, 多元响应
3 d6 U% o) W ~! l: }Multi-stage sampling, 多阶段抽样
0 x0 ^- _$ J% f0 G3 X' TMultivariate T distribution, 多元T分布 t/ }3 z; i. i" l
Mutual exclusive, 互不相容# F u' Y5 h' u( B6 K
Mutual independence, 互相独立1 l9 G0 G5 k4 X3 m }
Natural boundary, 自然边界
7 r7 m& W5 n. t) }Natural dead, 自然死亡: p) {( Y. S! m
Natural zero, 自然零
1 A, g3 U5 G! L; P; N0 A/ KNegative correlation, 负相关* t7 a9 t) ]) }6 A# @
Negative linear correlation, 负线性相关
) O* k* @' l6 B, I' ?3 P5 ENegatively skewed, 负偏9 H9 x8 e ]+ A4 f: E( ?
Newman-Keuls method, q检验8 D+ L/ M7 @1 U$ q! y
NK method, q检验
) D+ T2 b1 A9 j5 y' S. {No statistical significance, 无统计意义
2 }: f5 k! u6 G4 R9 `3 p( H9 q# f" _Nominal variable, 名义变量
) X, \, z7 X. |& a) L" b9 u% Z: I7 TNonconstancy of variability, 变异的非定常性
2 b% q9 j4 ]: F% V# bNonlinear regression, 非线性相关
2 g9 f1 J( U+ L- ], a- L: FNonparametric statistics, 非参数统计
, }' _2 f. U5 i5 Y* jNonparametric test, 非参数检验
" M5 N1 i# x8 Z$ f% t7 uNonparametric tests, 非参数检验
; W, n' {: }- T7 `. S8 FNormal deviate, 正态离差: h+ f9 U. k& F
Normal distribution, 正态分布
$ ?% R) U* S0 r* b/ ZNormal equation, 正规方程组
# j% B8 Z# E- r* A1 VNormal ranges, 正常范围( T. C ]0 W0 Y6 _
Normal value, 正常值4 C/ j4 e- q* \* j
Nuisance parameter, 多余参数/讨厌参数
, p3 B' h. V, z" iNull hypothesis, 无效假设
8 O. U, D7 b: q5 w4 NNumerical variable, 数值变量( Z$ Y1 ~7 Y+ B% h, H1 D* Z0 Q
Objective function, 目标函数
; C" z. H$ N [. _9 S% W+ ^9 H; N; Y5 sObservation unit, 观察单位
7 `5 s1 B$ E$ T. HObserved value, 观察值3 ~% b" T# d( |' J' c
One sided test, 单侧检验. D: _. `: Z5 a) M* t; F$ X
One-way analysis of variance, 单因素方差分析
. n, x* d8 B) H' O1 X; HOneway ANOVA , 单因素方差分析
& M+ A. U$ v- Q5 o4 [/ aOpen sequential trial, 开放型序贯设计' W" e2 H. Z0 U$ U6 P; V
Optrim, 优切尾
: m! l, Z# y. B/ M$ Q* ~Optrim efficiency, 优切尾效率
! f0 _: R: J+ Z' W+ c' kOrder statistics, 顺序统计量
) A: k, N; I. b# OOrdered categories, 有序分类
2 X: h. C! z0 Z# A% k- gOrdinal logistic regression , 序数逻辑斯蒂回归
0 _( C: W8 d1 F0 ZOrdinal variable, 有序变量. G' Y( \3 [* V* a2 q
Orthogonal basis, 正交基9 [5 F6 u. }% n2 O0 W2 A! Q3 q9 h
Orthogonal design, 正交试验设计& {& E m E! t" ]9 D, }. ~
Orthogonality conditions, 正交条件; H+ j5 |/ z1 U0 B8 s# l3 p
ORTHOPLAN, 正交设计
& R y3 z3 g m+ v' N) POutlier cutoffs, 离群值截断点
h( P0 o6 ~, f8 }, z$ K' \Outliers, 极端值
, h& }# g7 _' W! j& K( zOVERALS , 多组变量的非线性正规相关 & ~. w5 y) O! |$ ~& ~
Overshoot, 迭代过度
+ _; E/ N( h8 t1 Z! h! c9 f" c( B- OPaired design, 配对设计
& [, Z3 [/ D+ F0 rPaired sample, 配对样本
( V/ P, t% K9 N, M$ MPairwise slopes, 成对斜率6 T2 e( ]5 Q0 ~. x$ P. s- |
Parabola, 抛物线
5 e( N+ M: D5 [$ q- ?: s) U& ^Parallel tests, 平行试验
* d6 a# y' `# C M2 wParameter, 参数5 q! z" a, z, ?
Parametric statistics, 参数统计( F0 ~1 k& z2 W% H" p: C
Parametric test, 参数检验
* `! g8 l! g# k1 `5 p) LPartial correlation, 偏相关
6 q, d7 a- j: B7 qPartial regression, 偏回归
# i- K+ l" u1 \$ x2 R1 XPartial sorting, 偏排序
2 c+ @" {9 _2 f$ _' cPartials residuals, 偏残差
$ u U( I- d% y2 t+ J2 X. g! \Pattern, 模式
' d3 Y4 O2 ^2 d8 m: \. DPearson curves, 皮尔逊曲线
7 Q# q# e- m; m+ {! K# ?Peeling, 退层
) D( g% ?4 }, d k1 v8 uPercent bar graph, 百分条形图
$ f1 V5 K: O% x& m6 J+ VPercentage, 百分比
* i. v" [. c, [5 J! tPercentile, 百分位数
% t3 m1 O j5 G1 pPercentile curves, 百分位曲线
9 Y) o+ T! Y4 j. T3 q. KPeriodicity, 周期性
! T* i9 R4 x3 U: N0 Y- h- lPermutation, 排列
2 h' w1 J" z0 u* N) w$ s VP-estimator, P估计量* P5 v4 L2 Z1 m
Pie graph, 饼图
$ H* @2 D. I8 C" ZPitman estimator, 皮特曼估计量* D# \: Q( f+ H3 ^% W& @
Pivot, 枢轴量8 R7 i* [/ \# G3 @& S( u$ S
Planar, 平坦
% H, H2 {: U- BPlanar assumption, 平面的假设5 @- t$ v0 b# y5 x. {! H3 z
PLANCARDS, 生成试验的计划卡- T9 l2 a3 P8 s. Z1 }) n( A A6 T
Point estimation, 点估计7 v, G4 K' b. v/ s) F8 x% [5 y5 l
Poisson distribution, 泊松分布' c* n" z; u( H7 {
Polishing, 平滑
% R8 _/ o" q; J0 \5 Q, XPolled standard deviation, 合并标准差
# ~# N1 O' g" w4 E, E) CPolled variance, 合并方差2 U" J& N: B: s3 H4 \( B8 S5 U7 e" ]2 _
Polygon, 多边图
3 d3 F+ R9 d0 T2 g5 }( D+ U4 j4 V1 dPolynomial, 多项式, h5 ?% c9 {. n# h0 W( T3 B- T
Polynomial curve, 多项式曲线6 W8 E. z( q5 T( D* s
Population, 总体' p* _" i _, n
Population attributable risk, 人群归因危险度
3 v8 v7 K4 v$ J2 d8 aPositive correlation, 正相关
$ k. v* E7 N8 S% g& e; mPositively skewed, 正偏# D; l y8 `1 @! I' k% T
Posterior distribution, 后验分布) S1 D8 Z& W9 L1 I9 M) ]4 ?
Power of a test, 检验效能
# ?" p, J" c$ b* R3 s& b: ~6 vPrecision, 精密度- d1 t5 f; a0 e( s. N3 C) m" h
Predicted value, 预测值: V; U# K* c6 l5 d4 R
Preliminary analysis, 预备性分析
4 x4 Z6 K9 S% ~. ?2 iPrincipal component analysis, 主成分分析9 Y& f( ]* o$ R! U% k# R
Prior distribution, 先验分布" g! t9 `$ x, p' W& g7 l3 A8 x
Prior probability, 先验概率+ w, B; W; j2 h% j, y+ {
Probabilistic model, 概率模型
8 Z5 ^) _' A9 Q) v0 j; k$ R' H5 p' Rprobability, 概率2 J+ C; @3 Y2 z% c P0 \
Probability density, 概率密度9 A9 G7 Y+ a* N6 H! h
Product moment, 乘积矩/协方差
# i8 W2 ?% U7 Z' `4 m& o" O! [ GProfile trace, 截面迹图
; Y+ O( I0 B( T) i* F9 mProportion, 比/构成比* m9 T) C$ x$ g3 ~ M/ |7 z" g
Proportion allocation in stratified random sampling, 按比例分层随机抽样
4 j2 G0 ^0 J' g' V9 P' GProportionate, 成比例
) t4 B" E; }9 O* VProportionate sub-class numbers, 成比例次级组含量
+ M0 k4 \; V" p& u- rProspective study, 前瞻性调查9 D0 ?4 N8 n3 ?- t$ Z; H% A
Proximities, 亲近性
" C- G" k" S) x! A+ y, `; bPseudo F test, 近似F检验' ^ d4 g7 J: X5 k% V2 n
Pseudo model, 近似模型8 C5 e* b5 U2 ]+ Q( a
Pseudosigma, 伪标准差
; ?1 ^- H4 [5 S! \- F7 xPurposive sampling, 有目的抽样
/ D8 F1 V# G2 A& _8 JQR decomposition, QR分解
. B/ k* o- f; w0 Y# Q. q LQuadratic approximation, 二次近似$ P7 v, n5 r1 T: R% x
Qualitative classification, 属性分类! X$ P' S* w0 `9 ~8 \
Qualitative method, 定性方法) R) l6 C; }2 }- \. V4 T
Quantile-quantile plot, 分位数-分位数图/Q-Q图
) g5 c7 Q9 s( N' W7 H5 i, G- GQuantitative analysis, 定量分析5 H- A- X" N9 C4 f
Quartile, 四分位数
% b4 n* r) U9 H2 o) ~* ]Quick Cluster, 快速聚类
4 c2 a/ ~+ }+ r( i0 ~Radix sort, 基数排序
, g. D6 D8 H$ B7 X TRandom allocation, 随机化分组
K% P* R. w) g) eRandom blocks design, 随机区组设计+ K8 l0 ]6 e- [$ {. z* T
Random event, 随机事件6 T& f* Z- N+ [1 W2 D( h$ e
Randomization, 随机化
: K/ M/ N- w. U, eRange, 极差/全距
1 c+ ?$ k1 u. R8 gRank correlation, 等级相关
+ W: ~8 U* l9 P3 K5 URank sum test, 秩和检验
/ g0 U3 \$ Y, B s; URank test, 秩检验
; Z2 j8 |) g7 WRanked data, 等级资料
1 X! c' U) ?- {. BRate, 比率 ^# _, ^, n2 E# v& m
Ratio, 比例
* ~+ F6 U# s8 R# ~3 lRaw data, 原始资料' f& I2 j8 P# T+ }4 X G$ N0 C6 E8 e
Raw residual, 原始残差
5 N8 c7 w# X5 j) F) h8 k; cRayleigh's test, 雷氏检验; B ~0 m- _' q l, ]4 J+ q9 H% D( d
Rayleigh's Z, 雷氏Z值 * [) z1 r& j' b3 q
Reciprocal, 倒数/ L; |$ y8 w3 w! A6 c
Reciprocal transformation, 倒数变换
( c' B7 y( \& }+ H/ nRecording, 记录
B3 ^6 G. j. s8 l$ KRedescending estimators, 回降估计量2 [/ U: i2 L- g# `5 q
Reducing dimensions, 降维, k5 k% X# w" v9 H
Re-expression, 重新表达
) K) p9 c# E/ y0 i! k& a$ fReference set, 标准组+ p9 `' L# W( ?( \
Region of acceptance, 接受域' h& m1 b V( e! O. ~
Regression coefficient, 回归系数& m8 C# p8 q8 O- |9 p$ @3 a5 [
Regression sum of square, 回归平方和
7 R& C) L6 S3 T( Q" j9 k0 G% \Rejection point, 拒绝点
! {0 P2 i" V/ _0 P7 XRelative dispersion, 相对离散度& U1 r4 i! j1 g' w1 }$ K! h
Relative number, 相对数
! d6 r4 Q) X8 u8 D) F( [+ G% ^Reliability, 可靠性
* l0 d1 k) K9 t) K* Q& ZReparametrization, 重新设置参数
7 L2 J- W! m7 G& k& P bReplication, 重复
7 l* {! F7 ^7 D' u" Q$ L+ oReport Summaries, 报告摘要
# Z* [2 x2 y# }6 e4 X( Z2 E, SResidual sum of square, 剩余平方和
. l* t& J6 W3 i; }) S9 _7 ?Resistance, 耐抗性
I: P& U: r4 V+ K) R9 ?* ZResistant line, 耐抗线: ?# v. j) _1 p3 T5 N" p! k# x, n( d
Resistant technique, 耐抗技术
" d" F( ?2 Z. p0 Y* j IR-estimator of location, 位置R估计量
4 R+ ~7 n6 \- P8 v1 r" _R-estimator of scale, 尺度R估计量" v; p8 |, ]. Y% _
Retrospective study, 回顾性调查$ Y; D8 ]6 H* D0 \
Ridge trace, 岭迹
& _& q; i* M& ]- X }0 WRidit analysis, Ridit分析
( {5 ^; w; g; d% [( K) Z. cRotation, 旋转( T9 P4 A1 I( A4 z
Rounding, 舍入
6 z7 j9 D) p, b9 ~: g: uRow, 行* G% O4 {8 e/ O! \2 \& F" o J
Row effects, 行效应
) N, X8 z: M7 Y9 K, Z6 jRow factor, 行因素' \5 N; t8 z1 j; j
RXC table, RXC表
5 r- L( Q' z0 t: F" ]' f# `Sample, 样本
+ O- W$ ^! n' j+ bSample regression coefficient, 样本回归系数5 }0 `# j+ A& K% u+ V+ [
Sample size, 样本量
$ y p( b. O: \9 |. A( V( D* LSample standard deviation, 样本标准差) Y ]. `0 h s) a; N, V4 M* r
Sampling error, 抽样误差
4 t0 G* w. t, kSAS(Statistical analysis system ), SAS统计软件包! {- \9 ~ y% v+ m& {" p
Scale, 尺度/量表+ t5 [6 z: t5 G4 }" K3 O, {3 T
Scatter diagram, 散点图2 j- Z* A V. b! C
Schematic plot, 示意图/简图* q1 w* {4 x) X5 O7 L
Score test, 计分检验+ V% h# i! c! M
Screening, 筛检
: S9 A6 e+ [' F: `' R* BSEASON, 季节分析 9 f: Z+ V, d, R% K* P5 o
Second derivative, 二阶导数$ B9 [4 N( [& k3 v7 Y2 p7 E
Second principal component, 第二主成分* Q0 m" e7 f' M) i- I
SEM (Structural equation modeling), 结构化方程模型 9 O r. G) \8 |& T! G: r# f
Semi-logarithmic graph, 半对数图( S7 I0 }0 n, n% G& l
Semi-logarithmic paper, 半对数格纸
: l3 C. ]# o1 ~# S) \3 T! lSensitivity curve, 敏感度曲线
$ t! T' k+ M: i/ K; W" x+ X ^- m1 e0 pSequential analysis, 贯序分析" L5 d( L! z* Q/ P& H8 w9 m# k9 r
Sequential data set, 顺序数据集
0 V5 C! T! D6 H6 v6 C+ o- U. c) YSequential design, 贯序设计
2 d1 N! n1 r }* uSequential method, 贯序法
# X! l" r# w9 K3 T* H7 @& aSequential test, 贯序检验法9 n' G7 `1 |! S: Q+ A
Serial tests, 系列试验 z# ?& C( y. E |
Short-cut method, 简捷法
- P/ B( a, _" XSigmoid curve, S形曲线# Z w6 c% q$ V
Sign function, 正负号函数
[6 a/ a# V& G' q- e% GSign test, 符号检验- b, i3 c) {, W7 o" F9 d( a
Signed rank, 符号秩, H! u* G9 \9 b4 o3 A9 G
Significance test, 显著性检验
: S( T$ d1 I n+ OSignificant figure, 有效数字! `. S0 }# z7 ]1 s6 `6 j3 D
Simple cluster sampling, 简单整群抽样
) R& P$ e) d# x4 V0 w1 o2 i1 m: OSimple correlation, 简单相关
3 }2 h6 T, `8 h4 z( q& `+ W7 W, eSimple random sampling, 简单随机抽样
# \- O7 [/ l) d4 H5 O ]Simple regression, 简单回归3 o6 C" j% u8 s X) K# d
simple table, 简单表
- u8 \9 l; B' I# z! ]6 Y" iSine estimator, 正弦估计量, U& `% F x" r; J; {; w! n- c: W
Single-valued estimate, 单值估计
' l6 A ?+ Y: D8 p$ ISingular matrix, 奇异矩阵
]! v/ z# {- \$ w# s) pSkewed distribution, 偏斜分布
# [" o1 b4 [' ^% W! b. k. sSkewness, 偏度
7 d3 y% j1 N O4 s+ m# ZSlash distribution, 斜线分布2 X0 N' z4 e: |0 M
Slope, 斜率* a# D+ c8 d, g( N' y. x& a
Smirnov test, 斯米尔诺夫检验
% X! V9 D8 M$ Q7 G' l2 ?8 K8 bSource of variation, 变异来源
: u/ {) j8 v3 Y, \Spearman rank correlation, 斯皮尔曼等级相关
4 e: Y+ ?$ Z* L# A( YSpecific factor, 特殊因子
, y% b3 D0 ]; ^Specific factor variance, 特殊因子方差
5 ?5 t- u3 B2 k1 d5 WSpectra , 频谱' a8 c0 A) |) c3 h/ `( e; y
Spherical distribution, 球型正态分布. T) n- I7 n, A* H
Spread, 展布
4 D; s" P8 u k, l% H$ v! BSPSS(Statistical package for the social science), SPSS统计软件包
+ i8 p, w. g6 |9 }( G5 v$ p) p6 i5 ~Spurious correlation, 假性相关5 M, Q; k# k( X
Square root transformation, 平方根变换
; W/ r# H* _2 l& H9 E5 B+ r& oStabilizing variance, 稳定方差# H7 K. d- \ d' k' c' K
Standard deviation, 标准差- {2 o8 \( q% l) I2 ]0 @7 H+ Z) n# e
Standard error, 标准误5 Y- _2 }5 t- i Q2 w; m
Standard error of difference, 差别的标准误
( f3 n4 t9 i7 \Standard error of estimate, 标准估计误差) e% }2 D, S. W' S3 y+ U, P
Standard error of rate, 率的标准误$ U; F9 M. b$ E% U; C. {' V @/ d
Standard normal distribution, 标准正态分布
2 Z7 `6 N9 W T5 ~$ X0 UStandardization, 标准化+ }' t4 l3 `+ j7 d ?% m& N. q, f' w
Starting value, 起始值6 a# ^' X& G8 P3 ]- Q3 C6 n
Statistic, 统计量/ f( F$ C7 [6 {& g: ]$ E" I
Statistical control, 统计控制5 o2 h* b6 ^; j6 Y2 J3 w. z O
Statistical graph, 统计图* H; |& [' y! e& _( c
Statistical inference, 统计推断. h1 y9 ^. R6 C" l
Statistical table, 统计表
; N0 f' h' C( b6 TSteepest descent, 最速下降法8 O% y# r6 Y- S: {5 g* V1 s
Stem and leaf display, 茎叶图1 p3 H/ o# N, { _
Step factor, 步长因子
& r1 a. Z$ i# l( }Stepwise regression, 逐步回归3 x0 L3 T$ O0 S" l- S0 C
Storage, 存* S. J( A- N! M7 A+ b$ L
Strata, 层（复数）
0 t0 a9 n8 ?; N& J, UStratified sampling, 分层抽样1 j/ l! v$ I. R' S
Stratified sampling, 分层抽样
; h' t3 K a0 FStrength, 强度5 a9 B. u# s6 {
Stringency, 严密性1 ^( L. t- I: f7 O
Structural relationship, 结构关系
: @% Y+ g5 F6 dStudentized residual, 学生化残差/t化残差
: s# b& P2 z( j: HSub-class numbers, 次级组含量
1 Y; q, x- C# ]/ HSubdividing, 分割
' i% m# X5 m% C$ }& ~Sufficient statistic, 充分统计量
; T* U& G) \* S6 ~! USum of products, 积和; l Q9 W" q- @; ?. S
Sum of squares, 离差平方和# z3 v7 D( y' B- H
Sum of squares about regression, 回归平方和
7 l% `4 x2 o& QSum of squares between groups, 组间平方和
4 V& H: ^+ @* ^4 a1 J1 ~+ |Sum of squares of partial regression, 偏回归平方和- [4 `, Z, _$ h) o9 L
Sure event, 必然事件
( p3 ~" V/ H5 }/ A FSurvey, 调查
9 O1 m8 q0 l j* Z- V* s2 U3 JSurvival, 生存分析
/ {8 l! O# Y; S8 q8 ^8 [Survival rate, 生存率
) g& f, n/ N( w) N9 YSuspended root gram, 悬吊根图
r+ o7 q7 H! E5 f" CSymmetry, 对称
7 M9 W( {2 ^$ [% i* ?Systematic error, 系统误差2 D) i S: Y7 t5 N% Z/ g
Systematic sampling, 系统抽样7 ~& v! o: `8 C
Tags, 标签: F7 e/ _+ K1 P8 M
Tail area, 尾部面积8 V5 u' p6 F4 G3 v$ K( r) G
Tail length, 尾长
4 b9 V0 v2 m3 h5 X* t# sTail weight, 尾重$ I5 V% E6 \! |8 R. {" X
Tangent line, 切线
% A# T& G n7 K* s* i$ JTarget distribution, 目标分布* n x7 l! `- I/ G) l& b# `2 D
Taylor series, 泰勒级数
. ?) @: r3 Q8 g& b. RTendency of dispersion, 离散趋势
2 ?& j( h4 {/ j0 x: }Testing of hypotheses, 假设检验: ~5 A7 b; d' b- ` }) q
Theoretical frequency, 理论频数, v( a1 M9 j) s
Time series, 时间序列
2 B, _- o' K1 K; m2 L7 o2 gTolerance interval, 容忍区间
0 f3 c* v6 T. VTolerance lower limit, 容忍下限
5 X' u" U* x' BTolerance upper limit, 容忍上限
- ]8 c$ B7 d7 z3 a! Q; cTorsion, 扰率
5 l$ g$ m0 [, k5 d* o% D* kTotal sum of square, 总平方和
' h! f- S2 a" o2 C+ d tTotal variation, 总变异- V2 h1 H8 ^, K* E
Transformation, 转换: h% ?1 [/ |& ]$ f( @8 {
Treatment, 处理
, a% W9 `" d% e" y* e# Q9 tTrend, 趋势
+ p* m7 _+ ~4 q" ^; y2 e& ITrend of percentage, 百分比趋势* O" }$ v+ {" r- F# }" s' d- C3 |9 t
Trial, 试验9 V" v7 Y+ Y) j! y v4 l6 _1 O
Trial and error method, 试错法
! L; H% y7 T9 @, H0 M5 ^) _Tuning constant, 细调常数
# }5 |- M2 T- l. p) iTwo sided test, 双向检验
: H. h, }+ O; Q1 p1 BTwo-stage least squares, 二阶最小平方
# j- e0 ~+ q E, d) O) BTwo-stage sampling, 二阶段抽样
# h1 j8 v, d+ |5 f& X7 nTwo-tailed test, 双侧检验
" `. G+ C [& R8 Z! eTwo-way analysis of variance, 双因素方差分析
8 p( C" G/ g3 b9 ~ C& CTwo-way table, 双向表
, }! |5 U7 e' \8 M0 ^Type I error, 一类错误/α错误
j7 G- b( |/ y0 w! n5 jType II error, 二类错误/β错误1 j3 d0 a6 `* S" R' z
UMVU, 方差一致最小无偏估计简称
, T# {, T6 x; @" H# LUnbiased estimate, 无偏估计
' R V' Y1 q; SUnconstrained nonlinear regression , 无约束非线性回归: `' e5 i8 T. S
Unequal subclass number, 不等次级组含量
( o) n& |1 Y& R( M* i6 g! O! LUngrouped data, 不分组资料
" p3 I% C/ q& xUniform coordinate, 均匀坐标7 k2 e R+ {, s8 ~% ]0 L7 X) ]1 m
Uniform distribution, 均匀分布$ B5 l; ?. p: n. [6 _, j7 ^: ^
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计
8 n7 N3 h- c$ Z) H. n" |Unit, 单元7 [8 c5 H2 Q8 s, o4 u, V
Unordered categories, 无序分类
) h3 w" w1 {; V, j4 V" y' TUpper limit, 上限) Q: f3 ^0 }/ C6 q* f% l+ |
Upward rank, 升秩
6 C/ w' m. T: p RVague concept, 模糊概念4 @6 m4 z. _! h+ M& F
Validity, 有效性( L u9 r( z; i$ N X1 `+ c
VARCOMP (Variance component estimation), 方差元素估计
/ a& F6 U! M& Q, M) d( aVariability, 变异性4 a) N9 ?! g9 Y7 Z$ P2 t
Variable, 变量
& D" L6 p% s: YVariance, 方差
2 W3 I# Q7 G+ ]; H8 sVariation, 变异
( a! p0 b: F( S5 M4 S2 q6 |( ]9 l) `Varimax orthogonal rotation, 方差最大正交旋转
, p" ]; {/ W% T4 ]; O/ L! KVolume of distribution, 容积: C* l8 S! m, d
W test, W检验( K# ?8 W. S6 ]+ R
Weibull distribution, 威布尔分布$ e7 F, z f* N" N
Weight, 权数
- {& m f. A7 }7 O! N) A$ n% c( bWeighted Chi-square test, 加权卡方检验/Cochran检验/ u3 B5 k# C! i$ Z4 ^' i( P1 I
Weighted linear regression method, 加权直线回归
+ A. T/ u/ B4 e0 IWeighted mean, 加权平均数
+ Q9 R3 Z5 b8 f5 x; fWeighted mean square, 加权平均方差$ L; b8 F, z- z
Weighted sum of square, 加权平方和3 _$ g6 r& L& o- P
Weighting coefficient, 权重系数, r( J8 Z: `- y1 Q$ V: b9 |
Weighting method, 加权法
0 w! J& |0 ^5 \: w; RW-estimation, W估计量
/ b$ ?7 y1 j+ }" k. oW-estimation of location, 位置W估计量
' ^3 S9 N( M- C, I: T5 @* [6 |Width, 宽度) Q* M4 }2 n& i { n0 Y) F7 t, _
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验) s" W3 H0 X0 R7 L, S+ k
Wild point, 野点/狂点
3 D) w2 X% `0 G4 }9 QWild value, 野值/狂值
2 n+ {$ N! N) W+ XWinsorized mean, 缩尾均值
/ f# V. b' b" u; F% D+ H8 ?Withdraw, 失访
; b; R( H3 D8 O5 p' TYouden's index, 尤登指数3 j1 }$ D6 H0 Y. S9 S
Z test, Z检验# a; e( z: b+ H9 c6 I
Zero correlation, 零相关1 A, ~4 h- B I
Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
